Coral Reef Habitat Mapping: A Case Study In Mensanak Island- Senayang Lingga, Riau Province, Indonesia Methodology A Landsat 7 ETM+ image (path 125 row 60) that covered the study area, acquired on 6 September 2001 was used in this study. The image was system corrected using UTM 48 and WGS 84 as the projection and reference ellipsoid, respectively. The field survey (in situ) data is very important when working with remote sensing images. The field data will be used to compare ground feature and corresponding image feature. This study was concentrated on the reef top areas in which water depth varied between 0 - 5 m. The Rapid Reef Assessment (RRA) technique (COREMAP, 2001) was used in this study. Distribution of sampling reefs were determined using GIS to randomly allocate stations to sample on the reef top. The benthic data was recorded by the percentage coverage. Several enhancement techniques have been used in this study such as band ratio, principal component analysis (Khan et al., 1992) and water column correction (Mumby et al., 1998; Green et al., 2000). Unsupervised classification method using K-mean classification was carried out in this study based on the water column corrected image. To assign meaningful labels to the spectral classes, ground truth data was used. In this study, through the used of hierarchical cluster analysis and simple statistical approach (analysis of variance, ANOVA) as a guide to class amalgamation and selection of the final groups, which correspond with bottom types. The reliability of reef habitat classification has been tested using error matrix and kappa coefficient. Result and Discussion The complexity of coral reef habitats is one of the problems when dealing with mapping benthic habitats using remote sensing. The benthic communities where the reflectance spectral of the object commonly smaller than spatial resolution of view most satellite sensor (i.e. 30 m spatial resolution of Landsat 7), the spectral reflectance of the individual pixel will generally not represent the reflectance of single object but rather mixed of reflectance of two or more object present with ground resolution. Significant mixing of several different benthic types within relatively large pixels compounds the issue of classification inaccuracy. Because the complexity of the object represent in the ground resolution, some of the object are mixed together to make ease for the analysis. Spectral Characteristics of Benthic Habitat Analysis of spectral characteristics of benthic habitats is necessary for the classification of satellite data. Typical characteristics of benthic habitats (sand, substrate, live coral, sea grass and algae) in the study area were shown in the Figure 2. The analysis of spectral characteristic was based on relationship between band and Landsat ETM+ digital number (DN). This study found that sand bottoms had greater digital number for all bands. On the image bare sand areas are easily to determine, they appear very bright. On the other hand, sea grass/algae had greater digital number than live coral and live coral had greater digital number than substrate.  Figure 2. Spectral signature of benthic habitats Enhancement Technique The selection of color composite in this study was based on the calculation of Optimum Index Factor (OIF); band combination 123 has the highest OIF value. It can be explain because of those three bands have the capability of penetration into water column. The highest values of OIF show the most potential information contain in that combination Based on the OIF value we have been calculated band ratio and principal component analysis. Both techniques did not give good result. Ratio of band2/band 1 could be used for separating sand habitat and other habitats (live coral, algae, substrate and sea grass) and ratio band 3/band 1 shown more information of other benthic habitat such as live coral, sea grass and algae, but still difficult to separation among them. Using principal component analysis, the identification of benthic habitats was easier than using band ratio, which not only sand but also other benthic habitats such as coral, substrate and algae/sea grass can be identify. However, the separation of reef habitat zones still difficult or unclear border between zones has been found using PCA method. |